Back to Top

Paper Title

CUSTOMER SEGMENTATION USING K-MEANS CLUSTERING FOR TARGETED MARKETING IN BANKING

Keywords

  • customer segmentation
  • machine learning
  • k-means clustering
  • banking
  • targeted marketing
  • customer engagement

Article Type

Research Article

Issue

Volume : 3 | Issue : 2 | Page No : 89-94

Published On

September, 2024

Downloads

Abstract

Customer segmentation plays a pivotal role in the banking industry, allowing institutions to customize marketing strategies and offers for specific customer segments. This paper investigates the use of the K-Means clustering algorithm, a machine learning technique, to group customers based on crucial financial attributes including account balance, balance checking frequency, purchase patterns, cash advances, and purchase frequency. The objective is to form well-defined clusters that reveal distinct customer profiles. By harnessing these insights, banks can design targeted marketing campaigns and personalized offers, enhancing customer engagement, fostering loyalty, and ultimately driving profitability.

View more >>

Uploded Document Preview